Companies that run large-scale facilities such as warehouses or hospitals are interested in tracking their mobile assets in order to both maximize utilization and minimize theft. Other businesses, such as parking facilities and package distribution centers, also have the need to monitor, track, or find certain cars or packages within the confines of their respective infrastructures. Additionally, in many industries, there are also self-directed, robotic machines that move about in an industrial or hospital setting on a predetermined path and it could be useful to monitor and track these machines as well.
Specific to the hospital setting, for example, these mobile assets can include wheel chairs, mobile beds, IV pumps, and stretchers, etc. Interestingly, knowing the location of these items in a hospital can often also mean knowing the location of the patient, which can have significant value to the hospital administration and patient flow management personnel, while ensuring efficient operation and planning within a hospital.
Currently, it is known, as is discussed in U.S. Pat. No. 7,626,488, that the location of an organization's assets can be tracked using Radio Frequency Identification (RFID) tags. RFID tags are electronic devices that are comprised of a transponder and an integrated circuit programmed with unique identification information. These RFID tags are designed to communicate with tag readers, and, generally, have no internal power source, thus, relying on an external source to supply power. An RFID device with internal power is generally more expensive and bulkier than RFID devices without internal power. Additionally, a disadvantage of the RFID tracking is that as more devices are tracked, the less effective the tracking of the devices becomes, and the more complex and expensive it is to maintain the system. This is because a large amount of communication is required from the RFID tags to the readers, resulting in possible network bottlenecks, and because a large computational overhead is exerted on the center collecting these measurements. Moreover, the number of such centralized data collectors or stations does not scale with the number of tags.
The use of global positioning systems (GPS) to track objects is also well known and used everyday in the automotive and mobile phone industries, among others. GPS devices, however, are not preferred for indoor tracking due to the lack of line-of-sight communication with the satellites. Furthermore, GPS devices are not preferred in an indoor environment because they are relatively expensive and only accurate within several square yards, whereas, in an environment like a hospital or a nursing home, the tracking devices need to be accurate to a few feet.
Another commonly known communication system that can be used for monitoring and tracking is the wireless network. Often such a network is used in conjunction with RFID tags that are attached to the equipment to be monitored. Wireless transponders are used to collect sufficient information from the RFID tags and employ the received signal strength indicator (RSSI) and/or the time of arrival (ToA) information in order to triangulate the coordinates of a particular asset being tracked.
The key challenges in locating/tracking solutions for wireless indoor settings include: (i) the accuracy of distance estimates between sensors and anchors; (ii) the number of anchors (access points) required to guarantee certain accuracy; and (iii) the battery requirements of the sensors. In existing methodologies, the locating/tracking solutions do not employ sensor-to-sensor communication, but rely on sensor-to-anchor(s) communication. Due to this sensor-to-anchor(s) communication, the distance estimate(s) between sensor and anchor(s) is poor when the anchors are far away. Since all of the existing solutions in the field leverage sensor-to-anchor(s) communication, either the accuracy is poor due to heavy noise conditions when the number of anchors (access points) is small, or a large number of anchors (typically 5% of the objects or one at each room/zone to guarantee room/zone level accuracy) is required so that each sensor can find a reasonable number of anchors close-by. Furthermore, higher power is required to communicate with far-away anchors, and, to reduce this power, more anchors are required such that each sensor can find a reasonable number of anchors close-by.
What is needed is a system for tracking, monitoring, and locating mobile assets in a large-scale indoor facility, with low power requirements, that can handle a large number of mobile assets without the additional investment of adding anchors or related infrastructure, and can robustly handle communication imperfections (data loss, packet drops, interference, and multipath) within the system, while also providing acceptable accuracy and performance. The present invention improves upon the prior art in that the present invention locates and tracks objects accurately in an indoor environment using a very few number of anchors. The anchors are the devices that are fixed and have known exact locations. In the present invention, each asset is equipped with a sensing/computing device (herein referred to as a sensor) that is able to perform small computations and communicate over short distances ensuring minimal power requirements. The communication is required only with the sensors (assets) in a small neighborhood, thus reducing the high power required to communicate to the (possibly) far-away anchors, while also minimizing the communication bottlenecks, thereby reducing the need for the extra weight and additional maintenance needed for larger batteries. The present invention is robust to erroneous distance measurements, inter-sensor communication noise, and random data packet dropouts. Finally, the number of anchors needed for the system to work remains static no matter how many devices are being located.